This lab is currently in Beta — content may be updated as we refine the material
LABINTERMEDIATE

Local LLM with Ollama

Deploy Ollama locally, interact with multiple models, and build a Python client with streaming.

60 minutes
ai-bootcamp
Local LLM with Ollama - Platform Engineering Hands-On Lab Icon

Lab Overview

In this lab, you'll deploy a local LLM environment using Ollama and build a Python client that communicates with it.

You'll learn to:

  • Deploy and configure Ollama for local LLM inference
  • Pull and manage multiple model versions
  • Build a Python client that queries local models
  • Implement streaming responses for better UX
  • Compare model performance and select appropriate models

Prerequisites:

  • Python programming basics
  • Understanding of APIs and HTTP requests
  • Completion of previous AI Foundations labs

Key Concepts:

  • Local model inference vs cloud APIs
  • Ollama REST API
  • Streaming response patterns
  • Model selection criteria

What You'll Learn

Deploy and configure Ollama for local LLM inference

Manage multiple models with Ollama CLI

Build a Python client that queries local LLMs

Implement streaming responses using async generators

Prerequisites

ai-python-environment

basic-python

Technologies Covered

ollamallmpythonstreaminglocal-inference

Part of a Course

This lab is part of the AI Foundations for Infrastructure Engineers course

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